The AI Agent Playbook: Build Autonomous Systems That Sell For $10k+
Most "AI Agents" are just glorified chatbots that can't actually do anything.
You've tried Custom GPTs, but they stall when you need real-world actions like updating a CRM, scraping live data, or handling complex tickets. The gap between a cool demo and an enterprise-grade revenue generator is massive. This playbook bridges that gap — the exact architecture to build agents that execute workflows autonomously.
Inside this 81-page guide with 5 complete build tutorials:
Master the Agent Design Canvas, decide between No-Code (n8n) vs. Custom (LangChain/Python) using our decision tree, and deploy five specific agents: Research, Customer Service (RAG), Content, Sales Outreach, and Data Analysis. Plus the GUARD Framework to prevent hallucinations in production and the Agent Pricing Formula so you know what to charge.
What you'll build:
- Master the Agent Design Canvas to scope autonomous systems before writing a single line of code
- Deploy 5 Production-Ready Agents including a RAG Customer Support bot with human-handoff protocols
- Navigate the Tech Stack using the "Build-Buy-Connect" tree for n8n, LangChain, or CrewAI
- Implement the GUARD Framework to monitor agent safety and secure enterprise data
- Build a Research Agent that triggers search tools, synthesizes data, and formats reports autonomously
- Structure High-Ticket Offers using the "Audit-Build-Retainer" ladder for $10k+ agent services
- Connect Multi-Agent Systems where Sales Outreach hands off leads to Data Analysis automatically
- Calculate pricing with the Agent Pricing Formula — never underbid a complex project again
Who this is for:
Agency owners tired of selling low-ticket prompt engineering, developers mastering the n8n ecosystem, and consultants looking to charge $5k-$15k per implementation.
Battle-tested strategies from an instructor with 113K+ YouTube subscribers, 10K+ Udemy students, and Fortune 500 consulting experience.
Get the entire system for less than one hour of AI consulting.